Recollection and familiarity exhibit dissociable similarity gradients: a test of the complementary learning systems model.

Memory can often be triggered by retrieval cues that are quite different from the originally encoded events, but how different memory processes respond to variations in cue-target similarity is poorly understood. We begin by presenting simulations using a neurocomputational model of recognition memory (i.e., the complementary learning systems model), which proposes that the hippocampus supports recollection of associative information whereas the surrounding cortex supports assessments of item familiarity. The simulations showed that increases in the similarity between retrieval cues and learned items led to relatively linear increases in a cortex-based memory signal but led to steeper and more thresholded increases in the hippocampal signal. We then tested the predictions of the model by examining the effects of varying cue-target similarity in two recognition memory experiments in which participants studied a list of computer-generated faces and then, at test, gave confidence and remember/know responses to morphed faces. In both experiments, as cue-target similarity was increased, familiarity-based recognition increased in a gradual and relatively linear fashion, whereas recollection showed significantly steeper gradients. The results show that recollection and familiarity exhibit distinct similarity functions in recognition memory that correspond with predicted retrieval dynamics of the hippocampus and cortex, respectively.

Neurocomputational account of memory and perception: Thresholded and graded signals in the hippocampus.

Recent evidence suggests that the hippocampus, a region critical for long-term memory, also supports certain forms of high-level visual perception. A seemingly paradoxical finding is that, unlike the thresholded hippocampal signals associated with memory, the hippocampus produces graded, strength-based signals in perception. This article tests a neurocomputational model of the hippocampus, based on the complementary learning systems framework, to determine if the same model can account for both memory and perception, and whether it produces the appropriate thresholded and strength-based signals in these two types of tasks. The simulations showed that the hippocampus, and most prominently the CA1 subfield, produced graded signals when required to discriminate between highly similar stimuli in a perception task, but generated thresholded patterns of activity in recognition memory. A threshold was observed in recognition memory because pattern completion occurred for only some trials and completely failed to occur for others; conversely, in perception, pattern completion always occurred because of the high degree of item similarity. These results offer a neurocomputational account of the distinct hippocampal signals associated with perception and memory, and are broadly consistent with proposals that CA1 functions as a comparator of expected versus perceived events. We conclude that the hippocampal computations required for high-level perceptual discrimination are congruous with current neurocomputational models that account for recognition memory, and fit neatly into a broader description of the role of the hippocampus for the processing of complex relational information.

Testing a neurocomputational model of recollection, familiarity, and source recognition.

The authors assess whether the complementary learning systems model of the medial temporal lobes (Norman & O'Reilly, 2003) is able to account for source recognition receiver operating characteristics (ROCs). The model assumes that recognition reflects the contribution of a hippocampally mediated recollection process and a cortically mediated familiarity process. The hippocampal process is found to produce threshold output functions that lead to U-shaped zROCs, whereas the cortical process produces Gaussian signal detection functions and linear zROCs. The model is consistent with several dual process theories of recognition and is capable of producing the types of zROCs observed in studies of item and source recognition. In addition, the model makes the novel prediction that as the level of feature similarity across items increases, the ability of the hippocampus to encode distinct representations for each stimulus will diminish, and the threshold nature of recollection will break down, leading source zROCs to become more linear. The authors conducted 3 new behavioral source experiments that confirmed the model's prediction. The results demonstrate that the model provides a viable account of item and source recognition performance.